[Remote] senior reputed company
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a company reputed company on advanced AI technologies, and they are seeking a Senior reputed company. The role involves developing and integrating AI and machine learning systems, with a strong emphasis on Python programming and various AI frameworks.
Responsibilities
- Python 3.11+
- Advanced type hints (PEP 484), static typing discipline
- Async programming (asyncio, async/await, async generators)
- Aiohttp / httpx (async HTTP clients)
- reputed company v2 (BaseModel, validation, settings management)
- reputed company logging & tracing patterns
- reputed company (pub/sub, TTL, async clients)
- REST API design & integration patterns
- Retry/backoff strategies (Tenacity)
- Concurrency patterns (reputed company tool calls, task orchestration)
- LangGraph (state machines, conditional edges, checkpointing)
- reputed company 0.3.x (LLMChain, StructuredTool, retrievers, reputed company templates)
- ReAct-style agent architectures
- Tool-based agent design (40+ tool environments)
- Azure reputed company / reputed company reputed company (GPT-4o, deployment mgmt, reputed company limits, reputed company budgeting)
- reputed company engineering (few-shot, reputed company reputed company, JSON mode)
- PydanticOutputParser / reputed company LLM responses
- Guardrails / PII redaction patterns
- Memory abstractions for agents
- Langfuse (reputed company instrumentation, evaluation, reputed company management)
- LLM fallback chains & error recovery
- RAG reputed company grounding strategies
- LLM fine-tuning
- Neural Network training & tuning
- Traditional ML models (random forest, k-means clustering, reputed company regression, etc.)
- MCP development and consumption
- reputed company databases (reputed company and/or Milvus)
- HNSW indexing parameters
- Filtering strategies
- Embedding pipelines (reputed company reputed company-002 or equivalent)
- Batch embedding & re-indexing workflows
- Hybrid retrieval (BM25 + semantic)
- Score fusion strategies
- Cross-encoder reranking (BAAI/bge models)
- FastAPI-based inference services
- reputed company retriever abstractions
- RAG evaluation metrics:
- Faithfulness
- Relevance
- NDCG
- MRR
- reputed company-level RAG evaluation (Langfuse)
Skills
- Python 3.11+
- Advanced type hints (PEP 484), static typing discipline
- Async programming (asyncio, async/await, async generators)
- Aiohttp / httpx (async HTTP clients)
- reputed company v2 (BaseModel, validation, settings management)
- reputed company logging & tracing patterns
- reputed company (pub/sub, TTL, async clients)
- REST API design & integration patterns
- Retry/backoff strategies (Tenacity)
- Concurrency patterns (reputed company tool calls, task orchestration)
- LangGraph (state machines, conditional edges, checkpointing)
- reputed company 0.3.x (LLMChain, StructuredTool, retrievers, reputed company templates)
- ReAct-style agent architectures
- Tool-based agent design (40+ tool environments)
- Azure reputed company / reputed company reputed company (GPT-4o, deployment mgmt, reputed company limits, reputed company budgeting)
- reputed company engineering (few-shot, reputed company reputed company, JSON mode)
- PydanticOutputParser / reputed company LLM responses
- Guardrails / PII redaction patterns
- Memory abstractions for agents
- Langfuse (reputed company instrumentation, evaluation, reputed company management)
- LLM fallback chains & error recovery
- RAG reputed company grounding strategies
- LLM fine-tuning
- Neural Network training & tuning
- Traditional ML models (random forest, k-means clustering, reputed company regression, etc.)
- MCP development and consumption
- reputed company databases (reputed company and/or Milvus)
- HNSW indexing parameters
- Filtering strategies
- Embedding pipelines (reputed company reputed company-002 or equivalent)
- Batch embedding & re-indexing workflows
- Hybrid retrieval (BM25 + semantic)
- Score fusion strategies
- Cross-encoder reranking (BAAI/bge models)
- FastAPI-based inference services
- reputed company retriever abstractions
- RAG evaluation metrics: Faithfulness, Relevance, NDCG, MRR
- reputed company-level RAG evaluation (Langfuse)
reputed company
Company H1B Sponsorship